An alternative for the shallow networks in Eq. (REF ) which yields the same SE covariance was proposed in [1]}. With the feature vectors \(\omega _{1:n}\in \mathbb {R}^D\) , and the random variables \(w^c_{1:M}\)  and \(w^s_{1:M}\)  associated with the cosine and sine postactivation, respectively, we can write the random function as,
\(f({\bf x}) &= \frac{1}{\sqrt{n}}\sum _{i=1}^{n} w^c_i\cos (\omega _i\cdot {\bf x}) +w^s_i\sin (\omega _i\cdot {\bf x})\:,\\& = {\bf w}\Phi (\Omega {\bf x})\:,\) 
